1.1k citations · 1.6k across the 20 of their papers we have counts for
21 papers
Settling the Reward Hypothesis
Michael Bowling, John D. Martin, David Abel +1
The reward hypothesis posits that, "all of what we mean by goals and purposes can be well thought of as maximization of the expected value of the cumulative sum of a received scala…
Over-communicate no more: Situated RL agents learn concise communication protocols
Aleksandra Kalinowska, Elnaz Davoodi, Florian Strub +5
While it is known that communication facilitates cooperation in multi-agent settings, it is unclear how to design artificial agents that can learn to effectively and efficiently co…
The Alberta Plan for AI Research
Richard S. Sutton, Michael Bowling, Patrick M. Pilarski
Herein we describe our approach to artificial intelligence research, which we call the Alberta Plan. The Alberta Plan is pursued within our research groups in Alberta and by others…
Low-Variance and Zero-Variance Baselines for Extensive-Form Games
Trevor Davis, Martin Schmid, Michael Bowling
Extensive-form games (EFGs) are a common model of multi-agent interactions with imperfect information. State-of-the-art algorithms for solving these games typically perform full wa…
Ease-of-Teaching and Language Structure from Emergent Communication
Fushan Li, Michael Bowling
Artificial agents have been shown to learn to communicate when needed to complete a cooperative task. Some level of language structure (e.g., compositionality) has been found in th…
A Laplacian Framework for Option Discovery in Reinforcement Learning
Marlos C. Machado, Marc G. Bellemare, Michael Bowling
Representation learning and option discovery are two of the biggest challenges in reinforcement learning (RL). Proto-value functions (PVFs) are a well-known approach for representa…